Measuring Social Influence In Micro-blogs

Considering today’s rapid development of the Internet, social networks are playing an increasingly important role. The social network contains enormous amount of information, and all kinds of people are jumbled together, thereby, being able to identify the influence of different users is very meaningful in many areas, but also very challenging. User influence analysis is to use a mechanism to analyze the user information, and social behavior, which gives the influence of each user, so that you can find in the social network as a whole or in a small group, with a large influence of the user. However, the influence on the internal mechanism of network communication between nodes has no authoritative findings yet, mainly because of the lack of experimental research, which makes it very difficult to analyze user influence.This article first describes the user influence in traditional social network analysis research, there are two main areas:based on user’s analysis of the links between nodes and based on user behavior analysis. After it some latest research results on Twitter, a new form of social network, are introduced, which can be divided into link analysis and clustering method for two classes. Finally, we came up with our own method of user influence analysis based on the RT tree.By experimental analysis of large amounts of data on Twitter, we compared the results of several algorithms, and detailed analysis of the significance of the results.